31 citations · 104 across the 21 of their papers we have counts for
3 papers · 1 filter
Local and adaptive mirror descents in extensive-form games
Côme Fiegel, Pierre Ménard, Tadashi Kozuno +3
We study how to learn -optimal strategies in zero-sum imperfect information games (IIG) with trajectory feedback. In this setting, players update their policies sequentially bas…
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang +12
Mirror descent value iteration (MDVI), an abstraction of Kullback-Leibler (KL) and entropy-regularized reinforcement learning (RL), has served as the basis for recent high-performi…
Learning Generative Models with Goal-conditioned Reinforcement Learning
Mariana Vargas Vieyra, Pierre Ménard
We present a novel, alternative framework for learning generative models with goal-conditioned reinforcement learning. We define two agents, a goal conditioned agent (GC-agent) and…